1. What is Amazon Redshift?
Ans. Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. It’s one of the largest pay-as-you-go services in the cloud. It scales to petabytes of data and thousands of queries per second so you can get insights from your data to drive better business decisions.
2. When do we require Amazon Redshift?
Ans. Amazon Redshift is a fast, fully managed data warehouse service. Businesses can use it to obtain an easy-to-use cluster of web servers that work together as a single system to process and analyze large datasets in parallel without interrupting other business operations.
3. Which database does Amazon Redshift support?
Ans. It is based on PostgreSQL 8.0.2 Community Edition (Postgres), which Amazon has renamed to Amazon Redshift (the database engine will retain the Postgres compatibility).
4. What is the use of the AWS Redshift ODBC driver?
Ans. AWS Redshift is a hosted data warehouse service. The driver will allow you to connect to that database and import data into it for analytical purposes. This way, you can run complex queries on the imported data and slice and dice it as much as needed. By default, this connection requires SSL/TLS which means your credentials are never sent in the clear.
5. What is Massive Parallel Processing?
Ans. MPP is a technique of processing large data sets in parallel by breaking them into smaller chunks and distributing them among many nodes. The distributed nature of MPP databases makes it very ideal for analytics on large data sets. To put it in the simplest terms, when you request a query from Amazon Redshift, your query is sent to one of the many nodes in the cluster which processes it further and returns results back to you. The benefit of this distribution is that Amazon Redshift can handle lots of data quickly for complex queries.
6. What are some common analytics operations?
Ans. Some common use cases would be ad serving, clickstream analysis, business intelligence reporting, business metrics reporting, financial analysis etc.
7. What is AWS Redshift cluster Service?
Ans. A Redshift cluster is simply a group of computers that are connected together to act as one computer. Redshift clusters require at least two nodes in order to operate properly. Each node will have its own hard drive and CPU, but the same amount of computing power can be achieved by using half as many nodes with twice as much storage and capacity. The specific amount of storage is dependent on the number of nodes that are included in your cluster.
8. Is unstructured data supported in Amazon Redshift?
Ans. No, Amazon Redshift does not support unstructured or semi-structured data. Amazon Redshift is a petabyte-scale data warehouse that makes it simple and cost-effective to analyze all of your data using standard SQL and your existing Business Intelligence (BI) tools.
9. What are the benefits of Amazon Redshift?
Ans. The following are some of the benefits of Amazon Redshift:
1) Amazon Redshift’s Data Warehousing Technology can serve large data sets containing terabytes and petabytes of structured data to facilitate the analysis of any massive quantifiable data.
2) The technology is not based on a specific query language but rather a “data warehouse” management system using SQL syntax.
3) Redshift’s ability to work with a variety of data formats and file types makes it possible for users to easily take their existing business intelligence (BI) tools that support SQL-based analysis and use them without having to install any plugins or drivers.
4) Amazon Redshift is designed with data warehousing in mind. This means it has been optimized for processing large datasets containing structured, quantifiable information.
5) The technology allows companies to cut back on their costs while processing large amounts of data because it uses a scale-out architecture and can grow with you.
6) Amazon Redshift allows users to automate their data warehouse’s management tasks so they can focus on analysis and leave the heavy lifting up to the platform itself.
10. What are materialized views in amazon Redshift?
Ans. Materialized Views provide a way to make the results of a query against very large tables more efficient. You can create a materialized view using an existing table or a query in the same cluster. When you create a materialized view in Amazon Redshift, all updated and deleted rows in specific columns are tracked by Amazon Redshift. If any updated or deleted rows affect the data used in the materialized view’s query, then that data is updated when you refresh it.